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Description of Statistical Computation

Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_edabi.wasp
Title produced by softwareBivariate Explorative Data Analysis
Date of computationWed, 04 Nov 2009 03:57:59 -0700
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2009/Nov/04/t12573324171r49gzy82c6c1og.htm/, Retrieved Mon, 29 Apr 2024 13:42:25 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=53541, Retrieved Mon, 29 Apr 2024 13:42:25 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact143

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Trivariate Scatterplots] [Ws5] [2009-11-03 18:30:01] [ba905ddf7cdf9ecb063c35348c4dab2e]
- RMPD  [Partial Correlation] [WS5] [2009-11-03 18:33:47] [ba905ddf7cdf9ecb063c35348c4dab2e]
- RMPD    [Bivariate Explorative Data Analysis] [Bouwvergunningen ...] [2009-11-03 18:39:43] [ba905ddf7cdf9ecb063c35348c4dab2e]
-    D      [Bivariate Explorative Data Analysis] [werkloosheid mann...] [2009-11-04 10:37:31] [ba905ddf7cdf9ecb063c35348c4dab2e]
-    D          [Bivariate Explorative Data Analysis] [werkloosheid mann...] [2009-11-04 10:57:59] [244731fa3e7e6c85774b8c0902c58f85] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
1470
1849
1387
1592
1590
1798
1935
1887
2027
2080
1556
1682
1785
1869
1781
2082
2571
1862
1938
1505
1767
1607
1578
1495
1615
1700
1337
1531
1623
1543
1640
1524
1429
1827
1603
1351
1267
1741
1384
1392
1644
1661
1525
1718
1393
1784
1454
1344
1693
1393
1191
1340
1166
1238
1443
1279
1279
1651
Dataseries Y:
Download CSV
Histogram 
6.3
6.2
6.1
6.3
6.5
6.6
6.5
6.2
6.2
5.9
6.1
6.1
6.1
6.1
6.1
6.4
6.7
6.9
7
7
6.8
6.4
5.9
5.5
5.5
5.6
5.8
5.9
6.1
6.1
6
6
5.9
5.5
5.6
5.4
5.2
5.2
5.2
5.5
5.8
5.8
5.5
5.3
5.1
5.2
5.8
5.8
5.5
5
4.9
5.3
6.1
6.5
6.8
6.6
6.4
6.4

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'George Udny Yule' @ 72.249.76.132

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input & view raw input (R code)  \tabularnewline
Raw Output & view raw output of R engine  \tabularnewline
Computing time & 2 seconds \tabularnewline
R Server & 'George Udny Yule' @ 72.249.76.132 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=53541&T=0

[TABLE]
[ROW][C]Summary of computational transaction[/C][/ROW]
[ROW][C]Raw Input[/C][C]view raw input (R code) [/C][/ROW]
[ROW][C]Raw Output[/C][C]view raw output of R engine [/C][/ROW]
[ROW][C]Computing time[/C][C]2 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'George Udny Yule' @ 72.249.76.132[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=53541&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=53541&T=0

As an alternative you can also use a QR Code:  
QR Code


The GUIDs for individual cells are displayed in the table below:

Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'George Udny Yule' @ 72.249.76.132






Model: Y[t] = c + b X[t] + e[t]
c4.83619552559118
b0.000703463312301508

\begin{tabular}{lllllllll}
\hline
Model: Y[t] = c + b X[t] + e[t] \tabularnewline
c & 4.83619552559118 \tabularnewline
b & 0.000703463312301508 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=53541&T=1

[TABLE]
[ROW][C]Model: Y[t] = c + b X[t] + e[t][/C][/ROW]
[ROW][C]c[/C][C]4.83619552559118[/C][/ROW]
[ROW][C]b[/C][C]0.000703463312301508[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=53541&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=53541&T=1

As an alternative you can also use a QR Code:  
QR Code


The GUIDs for individual cells are displayed in the table below:

Model: Y[t] = c + b X[t] + e[t]
c4.83619552559118
b0.000703463312301508






Descriptive Statistics about e[t]
# observations58
minimum-0.891174074737068
Q1-0.396517705754219
median0.0146430489377154
mean-2.76527633406518e-17
Q30.333568902194967
maximum1.10509218939505

\begin{tabular}{lllllllll}
\hline
Descriptive Statistics about e[t] \tabularnewline
# observations & 58 \tabularnewline
minimum & -0.891174074737068 \tabularnewline
Q1 & -0.396517705754219 \tabularnewline
median & 0.0146430489377154 \tabularnewline
mean & -2.76527633406518e-17 \tabularnewline
Q3 & 0.333568902194967 \tabularnewline
maximum & 1.10509218939505 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=53541&T=2

[TABLE]
[ROW][C]Descriptive Statistics about e[t][/C][/ROW]
[ROW][C]# observations[/C][C]58[/C][/ROW]
[ROW][C]minimum[/C][C]-0.891174074737068[/C][/ROW]
[ROW][C]Q1[/C][C]-0.396517705754219[/C][/ROW]
[ROW][C]median[/C][C]0.0146430489377154[/C][/ROW]
[ROW][C]mean[/C][C]-2.76527633406518e-17[/C][/ROW]
[ROW][C]Q3[/C][C]0.333568902194967[/C][/ROW]
[ROW][C]maximum[/C][C]1.10509218939505[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=53541&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=53541&T=2

As an alternative you can also use a QR Code:  
QR Code


The GUIDs for individual cells are displayed in the table below:

Descriptive Statistics about e[t]
# observations58
minimum-0.891174074737068
Q1-0.396517705754219
median0.0146430489377154
mean-2.76527633406518e-17
Q30.333568902194967
maximum1.10509218939505


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 0 ; par2 = 36 ;
Parameters (R input):
par1 = 0 ; par2 = 36 ;
R code (references can be found in the software module):
par1 <- as.numeric(par1)
par2 <- as.numeric(par2)
x <- as.ts(x)
y <- as.ts(y)
mylm <- lm(y~x)
cbind(mylm$resid)
library(lattice)
bitmap(file='pic1.png')
plot(y,type='l',main='Run Sequence Plot of Y[t]',xlab='time or index',ylab='value')
grid()
dev.off()
bitmap(file='pic1a.png')
plot(x,type='l',main='Run Sequence Plot of X[t]',xlab='time or index',ylab='value')
grid()
dev.off()
bitmap(file='pic1b.png')
plot(x,y,main='Scatter Plot',xlab='X[t]',ylab='Y[t]')
grid()
dev.off()
bitmap(file='pic1c.png')
plot(mylm$resid,type='l',main='Run Sequence Plot of e[t]',xlab='time or index',ylab='value')
grid()
dev.off()
bitmap(file='pic2.png')
hist(mylm$resid,main='Histogram of e[t]')
dev.off()
bitmap(file='pic3.png')
if (par1 > 0)
{
densityplot(~mylm$resid,col='black',main=paste('Density Plot of e[t]   bw = ',par1),bw=par1)
} else {
densityplot(~mylm$resid,col='black',main='Density Plot of e[t]')
}
dev.off()
bitmap(file='pic4.png')
qqnorm(mylm$resid,main='QQ plot of e[t]')
qqline(mylm$resid)
grid()
dev.off()
if (par2 > 0)
{
bitmap(file='pic5.png')
acf(mylm$resid,lag.max=par2,main='Residual Autocorrelation Function')
grid()
dev.off()
}
summary(x)
load(file='createtable')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Model: Y[t] = c + b X[t] + e[t]',2,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'c',1,TRUE)
a<-table.element(a,mylm$coeff[[1]])
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'b',1,TRUE)
a<-table.element(a,mylm$coeff[[2]])
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable.tab')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Descriptive Statistics about e[t]',2,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'# observations',header=TRUE)
a<-table.element(a,length(mylm$resid))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'minimum',header=TRUE)
a<-table.element(a,min(mylm$resid))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Q1',header=TRUE)
a<-table.element(a,quantile(mylm$resid,0.25))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'median',header=TRUE)
a<-table.element(a,median(mylm$resid))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'mean',header=TRUE)
a<-table.element(a,mean(mylm$resid))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Q3',header=TRUE)
a<-table.element(a,quantile(mylm$resid,0.75))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'maximum',header=TRUE)
a<-table.element(a,max(mylm$resid))
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable.tab')